Articles | Volume 25, issue 9
Hydrol. Earth Syst. Sci., 25, 5105–5132, 2021
https://doi.org/10.5194/hess-25-5105-2021
Hydrol. Earth Syst. Sci., 25, 5105–5132, 2021
https://doi.org/10.5194/hess-25-5105-2021
Research article
22 Sep 2021
Research article | 22 Sep 2021

A comparison of tools and techniques for stabilising unmanned aerial system (UAS) imagery for surface flow observations

Robert Ljubičić et al.

Related authors

Towards harmonisation of image velocimetry techniques for river surface velocity observations
Matthew T. Perks, Silvano Fortunato Dal Sasso, Alexandre Hauet, Elizabeth Jamieson, Jérôme Le Coz, Sophie Pearce, Salvador Peña-Haro, Alonso Pizarro, Dariia Strelnikova, Flavia Tauro, James Bomhof, Salvatore Grimaldi, Alain Goulet, Borbála Hortobágyi, Magali Jodeau, Sabine Käfer, Robert Ljubičić, Ian Maddock, Peter Mayr, Gernot Paulus, Lionel Pénard, Leigh Sinclair, and Salvatore Manfreda
Earth Syst. Sci. Data, 12, 1545–1559, https://doi.org/10.5194/essd-12-1545-2020,https://doi.org/10.5194/essd-12-1545-2020, 2020
Short summary

Related subject area

Subject: Engineering Hydrology | Techniques and Approaches: Instruments and observation techniques
Identifying the optimal spatial distribution of tracers for optical sensing of stream surface flow
Alonso Pizarro, Silvano F. Dal Sasso, Matthew T. Perks, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 24, 5173–5185, https://doi.org/10.5194/hess-24-5173-2020,https://doi.org/10.5194/hess-24-5173-2020, 2020
Short summary
Technical note: Space–time analysis of rainfall extremes in Italy: clues from a reconciled dataset
Andrea Libertino, Daniele Ganora, and Pierluigi Claps
Hydrol. Earth Syst. Sci., 22, 2705–2715, https://doi.org/10.5194/hess-22-2705-2018,https://doi.org/10.5194/hess-22-2705-2018, 2018
Short summary
The June 2013 flood in the Upper Danube Basin, and comparisons with the 2002, 1954 and 1899 floods
G. Blöschl, T. Nester, J. Komma, J. Parajka, and R. A. P. Perdigão
Hydrol. Earth Syst. Sci., 17, 5197–5212, https://doi.org/10.5194/hess-17-5197-2013,https://doi.org/10.5194/hess-17-5197-2013, 2013
Development of a method of robust rain gauge network optimization based on intensity-duration-frequency results
A. Chebbi, Z. K. Bargaoui, and M. da Conceição Cunha
Hydrol. Earth Syst. Sci., 17, 4259–4268, https://doi.org/10.5194/hess-17-4259-2013,https://doi.org/10.5194/hess-17-4259-2013, 2013
Moving university hydrology education forward with community-based geoinformatics, data and modeling resources
V. Merwade and B. L. Ruddell
Hydrol. Earth Syst. Sci., 16, 2393–2404, https://doi.org/10.5194/hess-16-2393-2012,https://doi.org/10.5194/hess-16-2393-2012, 2012

Cited articles

Abdullah, L. M., Tahir, N. M., and Samad, M.: Video stabilization based on point feature matching technique, Proc. – 2012 IEEE Control Syst. Grad. Res. Colloquium, ICSGRC 2012, (Icsgrc), 303–307, https://doi.org/10.1109/ICSGRC.2012.6287181, 2012. 
Aguilar, W. G. and Angulo, C.: Real-time video stabilization without phantom movements for micro aerial vehicles, Eurasip J. Image Video Process., 2014, 1–13, https://doi.org/10.1186/1687-5281-2014-46, 2014a. 
Aguilar, W. G. and Angulo, C.: Robust video stabilization based on motion intention for low-cost micro aerial vehicles, 2014 IEEE 11th Int. Multi-Conference Syst. Signals Devices, SSD 2014, 1–6, https://doi.org/10.1109/SSD.2014.6808863, 2014b. 
Aguilar, W. G. and Angulo, C.: Real-Time Model-Based Video Stabilization for Microaerial Vehicles, Neural Process. Lett., 43, 459–477, https://doi.org/10.1007/s11063-015-9439-0, 2016. 
Alcantarilla, P., Nuevo, J., and Bartoli, A.: Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces, in Procedings of the British Machine Vision Conference 2013, British Machine Vision Association, 13.1–13.11, https://doi.org/10.5244/C.27.13, 2013. 
Download
Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.